Paper Citation Record · LEDGER

Measuring the Effects of Data Parallelism on Neural Network Training

As of 26 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:1811.03600.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1811.03600 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-26T06:30:07.085553+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T14:19:33.774814Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-05-25T14:20:55.408139Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation e066515e-4a52-4133-b1a8-7756e8e343b7 · inbound

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes cites this paper.

Large Batch Optimization for Deep Learning: Training BERT in 76 minutes Measuring the Effects of Data Parallelism on Neural Network Training

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-21T21:39:00.043658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation ad32e816-9d1b-4f0c-b9f9-9dcc26032a84 · inbound

Fast Training of Sparse Graph Neural Networks on Dense Hardware cites this paper.

Fast Training of Sparse Graph Neural Networks on Dense Hardware Measuring the Effects of Data Parallelism on Neural Network Training

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-25T14:20:55.411323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation f54c10a9-b956-4034-9cfa-811986e8bba2 · inbound

FinBERT: Financial Sentiment Analysis with Pre-trained Language Models cites this paper.

FinBERT: Financial Sentiment Analysis with Pre-trained Language Models Measuring the Effects of Data Parallelism on Neural Network Training

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T20:26:05.054403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 18c7010e-f418-48c2-99ab-756ad1d4fadb · inbound

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification cites this paper.

Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification Measuring the Effects of Data Parallelism on Neural Network Training

Reference 21

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T17:37:07.768937Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 3699be57-3190-4231-9656-4a60e1056e7f · inbound

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer cites this paper.

Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer Measuring the Effects of Data Parallelism on Neural Network Training

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-12T05:37:55.929334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 4cb72880-3f4a-4b97-ba58-7aeca5d2ea9d · inbound

Scaling Laws for Transfer cites this paper.

Scaling Laws for Transfer Measuring the Effects of Data Parallelism on Neural Network Training

Reference 106

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T00:58:13.782418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation ec5c4739-6616-4ddb-874b-7592b01828f1 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment Measuring the Effects of Data Parallelism on Neural Network Training

Reference 148

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:22:59.652392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 94ae50a6-440f-41f4-9c87-0c76996aef80 · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Measuring the Effects of Data Parallelism on Neural Network Training

Reference 225

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T15:42:47.891665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 1d9ff0b1-1624-45bf-afe7-f145a134d1b7 · inbound

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding cites this paper.

The Recurrent Transformer: Greater Effective Depth and Efficient Decoding Measuring the Effects of Data Parallelism on Neural Network Training

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-05-11T14:21:04.562340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.

Observation 54706af1-3a7f-4199-847d-ddb8b5cdefe5 · inbound

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization cites this paper.

How to Scale Mixture-of-Experts: From muP to the Maximally Scale-Stable Parameterization Measuring the Effects of Data Parallelism on Neural Network Training

Reference 70

Resolution: verified exact; local_arxiv, observed 2026-05-15T04:49:44.826609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-26T06:30:07.085553+00:00.